CN113343050A - Why-not problem solving method based on time perception object - Google Patents
Why-not problem solving method based on time perception object Download PDFInfo
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Abstract
The invention relates to a method for solving why-not problem based on a time perception object, which is used for solving why-not problem in time perception space keyword query, wherein the time perception space keyword query is expressed as q ═ q (q.loc, q.doc, q.t, q.k), wherein q.loc is query space position, q.doc is query keyword, q.t is query time and q.k is query return result quantity; the why-not problem solution method based on the time perception object comprises the following steps: obtaining an original query q ═ (q.loc, q.doc, q.t, q.k) and a missing object set M of the original query q; modifying q.doc, q.t and q.k in the original query q to q '. doc ', q '. t ' and q '. k ' such that the set of missing objects M appears in the query results of a refined query q ' (q.loc, q '. doc ', q '. t ', q '. k '); and calculating the modification cost of each refined query q ', and selecting the refined query q' with the minimum modification cost as the optimal refined query.
Description
Technical Field
The invention relates to the technical field of space keyword query, in particular to a method for solving the why-not problem based on a time perception object.
Background
In recent years, the availability of query results for databases has received a great deal of attention in the field of database research. In order to improve the usability of the database query result, Chapman and Jagadish originally proposed the why-not problem. Solving why-not is primarily to provide users with a reasonable explanation of why their desired objects do not appear in the query result set or to provide users with an effective solution for making certain data they desire appear in the query result set. For example, a user may search for top 3 steak restaurants on a popular comment, and as a result, he may find that restaurant A, which has passed through an environment that looks elegant and has good business, is not in the results returned from the query. At this time, will he want to inquire about how the returned three restaurants are really better than restaurant a in quality? Why is restaurant a not in the results of the query? Thereby reducing the confidence in the query results. Thus, the designer of the query algorithm needs to consider how to set the query parameters in order for restaurant A to appear in the query result set.
In the relevant literature and technical solutions for solving the why-not problem, a scheme of query modification is mainly adopted to solve the why-not problem. Since different query modification schemes need to be proposed for different query types, the related art cannot be directly applied to the why-not problem of the time-aware spatial keyword query. Therefore, it is desirable to propose a new and effective solution to the why-not problem of time-aware spatial keyword queries to improve the usability of such query results.
Disclosure of Invention
The embodiment of the invention provides a method for solving the why-not problem based on a time perception object, which aims to solve the problem that the why-not problem cannot be solved on the time perception space keyword query in the related technology.
A first aspect provides a solution to why-not problem based on a time-aware object, which is used to solve the why-not problem in a time-aware spatial keyword query, and the time-aware spatial keyword query is represented as q ═ q (q.loc, q.doc, q.t, q.k), where q.loc is query spatial position, q.doc is query keyword, q.t is query time, and q.k is number of results returned for the query; the why-not problem solution method based on the time perception object comprises the following steps: obtaining an original query q ═ (q.loc, q.doc, q.t, q.k) and a missing object set M of the original query q; modifying q.doc, q.t and q.k in the original query q to q '. doc ', q '. t ' and q '. k ' such that the set of missing objects M appears in the query results of a refined query q ' (q.loc, q '. doc ', q '. t ', q '. k '); and calculating the modification cost of each refined query q ', and selecting the refined query q' with the minimum modification cost as the optimal refined query.
In some embodiments, modifying q.doc, q.t and q.k in the original query q to q '. doc ', q '. t ' and q '. k ' such that the set of missing objects M appears in the query results of the refined query q ' ═ q.loc (q.loc, q '. doc ', q '. t ', q '. k ') comprises the steps of: calculating the missing object M in the missing object set MiRanking R (q', m) in the refined query qi) And determining the ranking R (q', M) of the missing object set M according to the ranking; causing the modification to satisfy the following condition: q ', doc'. N.D.M.C.not equal to phi; for any mi∈M，q’.t’∩miT' ≠ φ; q ', k' ═ R (q ', M), or R (q', M)<q ', k', and R (q ', M) ═ max (R (q', M)i) ); where M.doc is the query key of the missing object set M, MiT' is the missing object miThe effective time of (a).
In some embodiments, modifying q.doc, q.t and q.k in the original query q to q '. doc ', q '. t ' and q '. k ' such that the set of missing objects M appears in the query results of the refined query q ' ═ q.loc (q.loc, q '. doc ', q '. t ', q '. k ') comprises the steps of: under the first condition, the query end time q.et of the original query q is fixed and is in the value range (m.et, q.st)]Gradually increasing the query starting time q.st of the original query q; gradually reducing the value of the q.st by taking unit time as a step length; for candidate keyword set CSdocEnumerating the keywords in the (1) and adding the keywords selected by enumeration to the q.doc; the first condition is: l q.t | andn m.t | ≠ 0 and m.st<q.st<m.et<Et, where m.t is the valid time of the missing object m, m.st is the start time of the valid time of the missing object m, q.st is the query start time of the original query q, and m.et is the end time of the valid time of the missing object m; the set of candidate keywords CSdocThe conditions are satisfied: exist in the missing pairThe object's set of keywords and is not present in the original query's set of query keywords, and is represented as:
wherein m isiDoc for missing object miThe set of keywords.
In some embodiments, CS is applied to the candidate keyword setdocEnumerating the keywords in (1), and adding the keywords selected by enumeration to the q.doc, comprising the following steps: obtaining the candidate keyword set CSdocThe edit distance between each candidate keyword and the query keyword set q.doc of the original query; and arranging the editing distances from small to large.
In some embodiments, modifying q.doc, q.t and q.k in the original query q to q '. doc ', q '. t ' and q '. k ' such that the set of missing objects M appears in the query results of the refined query q ' ═ q.loc (q.loc, q '. doc ', q '. t ', q '. k ') comprises the steps of: under the second condition, the query time q.t of the original query is not modified, and only the query keyword q.doc and the query returned result number q.k of the original query are modified; calculating the missing object M in the missing object set MiRanking R (q', m) in the refined query qi) And determining the ranking R (q', M) of the missing object set M according to the ranking; the second condition is: l q.t | andn m.t | ≠ 0 and m.st<q.st，m.et>Et, where m.t is the valid time of the missing object m, m.st is the start time of the valid time of the missing object m, q.st is the query start time of the original query q, m.et is the end time of the valid time of the missing object m, and q.et is the query end time of the original query q.
In some embodiments, modifying q.doc, q.t and q.k in the original query q to q '. doc ', q '. t ' and q '. k ' such that the set of missing objects M appears in the query results of the refined query q ' ═ q.loc (q.loc, q '. doc ', q '. t ', q '. k ') comprises the steps of: under a third condition, fixing the query starting time q.st of the original query q, and gradually increasing the query ending time q.et of the original query q within a value range [ q.et, m.et ]; in units of time ofStep length is gradually increased to the value of the q.et; for candidate keyword set CSdocEnumerating the keywords in the (1) and adding the keywords selected by enumeration to the q.doc; the third condition is: l q.t | andn m.t | ≠ 0 and q.st<m.st<q.et<Et, where m.t is the valid time of the missing object m, m.st is the start time of the valid time of the missing object m, q.st is the query start time of the original query q, m.et is the end time of the valid time of the missing object m, and q.et is the query end time of the original query q.
In some embodiments, modifying q.doc, q.t and q.k in the original query q to q '. doc ', q '. t ' and q '. k ' such that the set of missing objects M appears in the query results of the refined query q ' ═ q.loc (q.loc, q '. doc ', q '. t ', q '. k ') comprises the steps of: under the fourth condition, the query ending time q.et of the original query q is fixed, and the query starting time q.st of the original query q is gradually reduced within a value range (m.st, m.et); gradually reducing the value of the q.st by taking unit time as a step length; for candidate keyword set CSdocEnumerating the keywords in the (1) and adding the keywords selected by enumeration to the q.doc; the fourth condition is: l q.t | andgate m.t | ═ 0 and m<And q.st, wherein m.t is the effective time of the missing object m, m.st is the starting time of the effective time of the missing object m, q.st is the query starting time of the original query q, and m.et is the ending time of the effective time of the missing object m.
In some embodiments, modifying q.doc, q.t and q.k in the original query q to q '. doc ', q '. t ' and q '. k ' such that the set of missing objects M appears in the query results of the refined query q ' ═ q.loc (q.loc, q '. doc ', q '. t ', q '. k ') comprises the steps of: under the fifth condition, the query starting time q.st of the original query q is fixed, and the query ending time q.et of the original query q is gradually increased within a value range [ q.et, m.et ]; gradually increasing the value of the q.et by taking unit time as a step length; the fifth condition is: l q.t | andno m.t | -0 and q.et < m.st, where m.t is the valid time of the missing object m, m.st is the start time of the valid time of the missing object m, and q.et is the query end time of the original query q.
In some embodiments, calculating a modification cost for each of said refined queries q' comprises the steps of: calculating a modification cost of the refined query q' according to a first formula; selecting the refining query q' with the minimum modification cost as the optimal refining query; the first formula:
the penalty (q, q ') is the modification cost of the refined query q ', namely the modification cost from the original query q to the refined query q '; lambda [ alpha ]1、λ2、λ3Respectively representing the modification preference parameters of the user for the query return result quantity q.k, the query keyword q.doc and the query time q.t, and setting lambda to be more than or equal to 0 and less than or equal to lambda1，λ2，λ31 or less and lambda1+λ2+λ3＝1；Δk＝max(0,k’-k)，ΔkmaxIs the maximum modifier of q.k and is used to normalize Δ k to the interval [0,1 ]](ii) a Δ doc denotes the edit distance modified from q.doc to q '. doc' | Δ docmax| represents the maximum modification operation from q.doc to q.doc @ m.doc,
|Δdocmaxi for normalizing Delta doc to the interval [0,1 ]](ii) a Δ t denotes the modifier from q.t to q '. t', Δ tmaxRepresenting the maximum modification, at, over timemaxFor normalizing Δ t to the interval [0,1 ]]。
In some embodiments, quantizing the modification cost from the original query q to the refined query q' according to a first formula includes the steps of:
let Δ kmax＝max(Rm-k, 1), wherein Rm＝R(q’,M)＝max(R(q’,mi))。
In some embodiments, quantizing the modification cost from the original query q to the refined query q' according to a first formula includes the steps of:
make it
Where xi is the same as [0,1 ]]Q.et is the query ending time of the original query, q.st is the query starting time of the original query, q '. et' is the query ending time of the refined query, and q '. st' is the query starting time of the refined query;
make it
The technical scheme provided by the invention has the beneficial effects that:
the embodiment of the invention provides a method for solving the why-not problem based on time perception objects, and a new query (refined query) q '(q.loc, q'. doc ', q.t', q '. k') is obtained by modifying q.doc, q.t and q.k of an original query simultaneously, so that all missing objects appear in a result set of the new query. The problem that why-not can not be solved on the time-aware spatial keyword query in the related art can be solved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic flow chart of a solution to the why-not problem based on temporal perceptual objects according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a system for solving the why-not problem based on a temporal perceptual object according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
The embodiment of the invention provides a method for solving the why-not problem based on a time perception object, which aims to solve the problem that the why-not problem cannot be solved on the time perception space keyword query in the related technology. The time-aware spatial keyword query is denoted as q ═ q.loc, q.doc q.t, q.k, where q.loc is the query spatial location, q.doc is the query keyword, q.t is the query time, and q.k is the query return result number;
as shown in fig. 1, the why-not problem solution based on the time perception object comprises the following steps:
s100, obtaining an original query q ═ (q.loc, q.doc, q.t, q.k) and a missing object set M of the original query q;
modifying q.doc, q.t and q.k in the original query q into q '. doc ', q '. t ' and q '. k ', so that the missing object set M appears in the query result of a refined query q ' (q.loc, q '. doc ', q '. t ', q '. k ');
and S300, calculating the modification cost of each refining query q ', and selecting the refining query q' with the minimum modification cost as the optimal refining query.
It should be noted that, when defining a time-aware spatial keyword query, it is assumed that an edge E of a road network G has a group of spatio-temporal text objects O E O, and each object O represents an interest point and has 3 attributes: loc, o.doc, o.t, where o.loc denotes the location of object o, pairLike o to its side (v)i,vj) Can be respectively expressed as | viO and o, vjAnd object oiAnd ojThe distance between the road networks is o on the road networkiAnd ojThe length of the shortest path between the query location q.loc and the query location q.loc of the user is usually determined, and the query location q.loc is not modified in the embodiment. Doc is a set of keywords (e.g., Sunshine store) used to describe an object o, and its formalization is defined as o1,f1)，(o.key2,f2)，...，(o.keyn,fn) Therein, keyiIs the ith key, f, describing object oiIs o.keyiThe frequency of occurrence in the description of object o. o.t denotes the valid time of the object o (e.g., the Sunshine store has an open time of 9:00-19:00), which can be formally defined as o.t ═ o.st, o.et, where o.st denotes the start time of the valid time of the object o and o.et denotes the end time of the valid time of the object o. A missing object set M ═ M is also defined1,m2,...,mnIn which m isi∈M，miIs a missing object.
In order to make all the missing objects appear in the result set of the new query, the present embodiment proposes a method of obtaining a new query (refined query) q '(q.loc, q'. doc ', q'. t ', q.k') by modifying q.doc, q.t and q.k of the original query simultaneously, which is more effective and less costly than a method of modifying one parameter individually.
In one embodiment, step S200 further comprises calculating the missing object M in the missing object set MiRanking R (q', m) in the refined query qi) And determining the ranking R (q', M) of the missing object set M according to the ranking; and the modification is made to satisfy the following condition:
q’.doc’∩M.doc≠φ；
for any mi∈M，q’.t’∩mi.t’≠φ；
q ', k ' ═ R (q ', M), orR(q’,M)<q ', k', and R (q ', M) ═ max (R (q', M)i))；
Where M.doc is the query key of the missing object set M, MiT' is the missing object miThe effective time of (a).
Further, temporal-aware spatial keyword query in a traffic road network [ J ] can be performed by a temporal-aware spatial keyword query algorithm (which may be the paper "Youqinghua, Liyanhong, Huangliang, etc. ]]The TIK algorithm mentioned in "university of south-central ethnic university" 2021,40(2) ", or other algorithms for performing time-aware spatial keyword queries) finds each missing object M in the set MiAnd calculates the missing object miRanking R (q, m) in original query qi) To determine the rank R (q, M) of the missing object set M in the original query q; then enumerate all candidate keyword sets CS as much as possibledocAnd an optimizable time interval (the maximum range that query time q.t can be modified) yields all possible refinement queries q'; and then for each refined query q ', calling the time-aware spatial keyword query algorithm to determine R (q', M).
In one embodiment, S200 further comprises the steps of:
s201: under a first condition, fixing the query ending time q.et of the original query q, and gradually increasing the query starting time q.st of the original query q within a value range (m.et, q.st);
s202: gradually reducing the value of the q.st by taking unit time as a step length;
s203: for candidate keyword set CSdocEnumerating the keywords in the (1) and adding the keywords selected by enumeration to the q.doc;
the first condition is: l q.t | andn m.t | ≠ 0 and m.st < q.st < m.et < q.et, wherein m.t is the effective time of the missing object m, m.st is the starting time of the effective time of the missing object m, q.st is the query starting time of the original query q, and m.et is the ending time of the effective time of the missing object m;
the set of candidate keywords CSdocThe conditions are satisfied: keywords present in missing objectsIn the set and not in the set of query keywords of the original query, and is represented as:
It should be noted that, since the larger the effective time interval overlap rate Tolap (q.t, m.t) of the query time interval and the missing object m is, the more likely the missing object m is included in the result of the query, the modification (reduction of the time length of the query or increase of the time interval in which the query time intersects the effective time of the missing object m) of the query time interval may be adopted to increase the time interval overlap rate Tolap (q.t, m.t) of the query time interval and the missing object m. In this embodiment, the end time q.et of the original query is fixed, the start time q.st of the original query is advanced, and when the start time q.st of the original query is advanced to be close to m.st, the overlapping rate of the query time and the effective time of the missing object is increased, so that the overlapping rate of the query time interval and the time interval of the missing object m, namely, the overlap rate of the query time interval and the time interval of the missing object m, is increased (q.t, m.t).
Preferably, in order to facilitate enumeration of q.st, 0.5h is used as the step size for decreasing the value of q.st.
Preferably, the query key q.doc can be modified from the CSdocEnumerating keywords to increase the text similarity of the query keywords to the keywords of the missing object. When query times q.t and q.k are determined, the smaller Δ doc, the smaller the cost of modification. Therefore, in order to make the query more efficient, step S203 further includes the steps of:
s203 a: obtaining the candidate keyword set CSdocThe edit distance between each candidate keyword and the query keyword set q.doc of the original query;
s203 b: arranging the editing distances from small to large;
it can be understood that, based on the above steps S203a and S203b, the keyword with a small editing distance from q.doc is easier to select, resulting in a smaller modification cost.
In one embodiment, S200 includes the steps of:
s204, under the second condition, the query time q.t of the original query is not modified, and only the query keyword q.doc of the original query and the query return result number q.k are modified;
s205, calculating the missing object M in the missing object set MiRanking R (q', m) in the refined query qi) And determining the ranking R (q', M) of the missing object set M according to the ranking;
the second condition is: l q.t | andd m.t | ≠ 0 and m.st < q.st, m.et > q.et, wherein m.t is the valid time of the missing object m, m.st is the start time of the valid time of the missing object m, q.st is the query start time of the original query q, m.et is the end time of the valid time of the missing object m, and q.et is the query end time of the original query q.
When m.st is expressed, it is noted that<q.st and m.et>Et is
When the method of reducing the value of q.t is adopted, the ranking of the missing objects m is not affected, and the modifier Δ t from q.t to q '. t' is generated>0, making the cost of modifying the query large; increasing | q.t | increases the number of objects retrieved in searching the space, and when | q.t | fly>And | m.t, the spatiotemporal text similarity rank (q, m) of the missing object m under the original query q is obviously reduced, so that the rank R (q, m) of the missing object m is back. Therefore, neither decreasing | q.t | nor increasing | q.t | will result in an optimal refined query q', so the fixed query time q.t in the modified query is chosen to be the original query time q.t, and only the keywords q.doc of the original query and the number of query results q.k are adjusted.
In one embodiment, S200 further comprises the steps of:
s206: under a third condition, fixing the query starting time q.st of the original query q, and gradually increasing the query ending time q.et of the original query q within a value range [ q.et, m.et ];
s207: gradually increasing the value of the q.et by taking unit time as a step length;
s208: for candidate keyword set CSdocEnumerating the keywords in the (1) and adding the keywords selected by enumeration to the q.doc;
the third condition is: l q.t ≠ m.t | ≠ 0 and q.st < m.st < q.et < m.et, where m.t is the valid time of the missing object m, m.st is the start time of the valid time of the missing object m, q.st is the query start time of the original query q, m.et is the end time of the valid time of the missing object m, and q.et is the query end time of the original query q.
In one embodiment, S200 further comprises the steps of:
s209: under the fourth condition, the query ending time q.et of the original query q is fixed, and the query starting time q.st of the original query q is gradually reduced within a value range (m.st, m.et);
s210: gradually reducing the value of the q.st by taking unit time as a step length;
s211: for candidate keyword set CSdocEnumerating the keywords in the (1) and adding the keywords selected by enumeration to the q.doc;
the fourth condition is: where | q.t |, andgate m.t | ═ 0 and m.et < q.st, where m.t is the valid time of the missing object m, m.st is the start time of the valid time of the missing object m, q.st is the query start time of the original query q, and m.et is the end time of the valid time of the missing object.
In one embodiment, S200 further comprises the steps of:
s212: under the fifth condition, the query starting time q.st of the original query q is fixed, and the query ending time q.et of the original query q is gradually increased within a value range [ q.et, m.et ];
s213: gradually increasing the value of the q.et by taking unit time as a step length;
the fifth condition is: l q.t | andno m.t | -0 and q.et < m.st, where m.t is the valid time of the missing object m, m.st. is the start time of the valid time of the missing object m, and q.et is the query end time of the original query q.
The why-not problem solving method based on the time perception object provided by the embodiment of the invention considers that: 1) the enumeration range of the time interval is too large, so that the efficiency of enumerating all the selectable time intervals by adopting a general enumeration mode is too low; 2) the possibility that the query modification quality cannot be guaranteed exists when the original query is modified by extracting a part of time intervals from the whole time space through a sampling method, and meanwhile, a time-aware spatial keyword query algorithm needs to be called again for each enumerated time interval and keyword in the process of searching the missing object m, so that excessive calculation and I/O (input/output) expenses are caused. To solve these problems, the efficiency of enumerating the refined query q' is improved by using the overlap rate Tolap (q.t, m.t) of the effective time intervals of the query time interval and the missing object m, thereby overcoming the above-mentioned problems and improving the efficiency of solving the why-not problem of the time-aware spatial keyword query.
In one embodiment, S300 further comprises the steps of:
s301: calculating a modification cost of the refined query q' according to a first formula;
s302: selecting the refining query q' with the minimum modification cost as the optimal refining query;
the first formula:
the penalty (q, q ') is the modification cost of the refined query q ', namely the modification cost from the original query q to the refined query q ';
λ1、λ2、λ3respectively representing the modification preference parameters of the user for the query return result quantity q.k, the query keyword q.doc and the query time q.t, and setting lambda to be more than or equal to 0 and less than or equal to lambda1，λ2，λ31 or less and lambda1+λ2+λ3＝1；
Δk＝max(0,k’-k)，ΔkmaxIs the maximum modifier of q.k and is used to normalize Δ k to the interval [0,1 ]]；
Δ doc denotes the edit distance from q.doc to q'. doc，|Δdocmax| represents the maximum modification operation from q.doc to q.doc @ m.doc,
|Δdocmaxi for normalizing Delta doc to the interval [0,1 ]]；
Δ t denotes the modifier from q.t to q '. t', Δ tmaxRepresenting the maximum modification, at, over timemaxFor normalizing Δ t to the interval [0,1 ]]。
Note that |. DELTA.docmaxThe | can be calculated by the edit distance, and Δ t can contain the missing object in the result set by modifying the start time and the end time of the query.
Preferably, let Δ kmax＝max(Rm-k, 1), wherein Rm＝R(q’,M)＝max(R(q’,mi))。
Preferably, considering that the modification of the start time and the end time may result in a change of the original time interval length, therefore:
make it
Where xi is the same as [0,1 ]]Q.et is the query ending time of the original query, q.st is the query starting time of the original query, q '. et' is the query ending time of the refined query, q '. st' is the query starting time of the refined query,
represents a translation of the time interval and (q '. et-q'. st) - (q.et-q.st) represents a modification of the length of the time interval;
make it
In some embodiments, in finding a missing object m, if the refined query q "retrieves
If there are objects, but not all missing objects in M, then q "is not an optimal optimized query, and the refined query q" is not considered directly. Wherein p iscThe cost of the query q' is refined for the current optimum. In this way, inappropriate refinement queries can be directly filtered out so that unnecessary search processes can be ended in advance, thereby improving the efficiency of the search process.
The embodiment of the present invention further provides a system for solving the why-not problem based on a time-aware object, where the time-aware spatial keyword query is represented by q ═ (q.loc, q.doc, q.t, q.k), where q.loc is a query spatial location, q.doc is a query keyword, q.t is a query time, and q.k is a query return result number;
as shown in fig. 2, the system includes:
a query obtaining module for obtaining an original query q ═ (q.loc, q.doc, q.t, q.k) and a missing object set M of the original query q;
a query modification module for modifying q.doc, q.t and q.k in the original query q to q '. doc', q '. t and q'. k ', such that the missing object set M appears in the query results of a refined query q' ═ q.loc, q '. doc', q '. t', q '. k');
and the query selection module is used for calculating the modification cost of each refined query q 'and selecting the refined query q' with the minimum modification cost as the optimal refined query.
In some embodiments, the query selection module is further to:
calculating a modification cost of the refined query q' according to a first formula;
selecting the refining query q' with the minimum modification cost as the optimal refining query;
the first formula:
the penalty (q, q ') is the modification cost of the refined query q ', namely the modification cost from the original query q to the refined query q ';
λ1、λ2、λ3respectively representing the modification preference parameters of the user for the query return result quantity q.k, the query keyword q.doc and the query time q.t, and setting lambda to be more than or equal to 0 and less than or equal to lambda1，λ2，λ31 or less and lambda1+λ2+λ3＝1；
Δk＝max(0,k’-k)，ΔkmaxIs the maximum modifier of q.k and is used to normalize Δ k to the interval [0,1 ]]；
Δ doc denotes the edit distance modified from q.doc to q '. doc' | Δ docmax| represents the maximum modification operation from q.doc to q.doc @ m.doc,
|Δdocmaxi for normalizing Delta doc to the interval [0,1 ]]；
Δ t denotes the modifier from q.t to q '. t', Δ tmaxRepresenting the maximum modification, at, over timemaxFor normalizing Δ t to the interval [0,1 ]]。
In the description of the present invention, it should be noted that the terms "upper", "lower", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, which are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and operate, and thus, should not be construed as limiting the present invention. Unless expressly stated or limited otherwise, the terms "mounted," "connected," and "connected" are intended to be inclusive and mean, for example, that they may be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
It is to be noted that, in the present invention, relational terms such as "first" and "second", and the like, are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The foregoing are merely exemplary embodiments of the present invention, which enable those skilled in the art to understand or practice the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method for solving why-not problem based on time perception object, which is characterized in that the method is used for solving why-not problem in time perception space keyword query, and the time perception space keyword query is expressed as q ═ q (q.loc, q.doc, q.t, q.k), wherein q.loc is query space position, q.doc is query keyword, q.t is query time and q.k is query return result number;
the why-not problem solution method based on the time perception object comprises the following steps:
obtaining an original query q ═ (q.loc, q.doc, q.t, q.k) and a missing object set M of the original query q;
modifying q.doc, q.t and q.k in the original query q to q '. doc ', q '. t ' and q '. k ' such that the set of missing objects M appears in the query results of a refined query q ' (q.loc, q '. doc ', q '. t ', q '. k ');
and calculating the modification cost of each refined query q ', and selecting the refined query q' with the minimum modification cost as the optimal refined query.
2. The method for solving the why-not problem based on temporal perceptual objects as defined in claim 1,
modifying q.doc, q.t and q.k in the original query q to q '. doc ', q '. t ' and q '. k ' such that the missing object set M appears in the query results of a refined query q ' (q.loc, q '. doc ', q '. t ', q '. k '), comprising the steps of:
calculating the missing object M in the missing object set MiRanking R (q', m) in the refined query qi) And determining the ranking R (q', M) of the missing object set M according to the ranking;
causing the modification to satisfy the following condition:
q’.doc’∩M.doc≠φ；
for any mi∈M，q’.t’∩mi.t’≠φ；
q ', k' ═ R (q ', M), or R (q', M)<q ', k', and R (q ', M) ═ max (R (q', M)i))；
Where M.doc is the query key of the missing object set M, MiT' is the missing object miThe effective time of (a).
3. The method for solving the why-not problem based on temporal perceptual objects as defined in claim 1,
modifying q.doc, q.t and q.k in the original query q to q '. doc ', q '. t ' and q '. k ' such that the missing object set M appears in the query results of a refined query q ' (q.loc, q '. doc ', q '. t ', q '. k '), comprising the steps of:
under a first condition, fixing the query ending time q.et of the original query q, and gradually increasing the query starting time q.st of the original query q within a value range (m.et, q.st);
gradually reducing the value of the q.st by taking unit time as a step length;
for candidate keyword set CSdocEnumerating the keywords in the (1) and adding the keywords selected by enumeration to the q.doc;
the first condition is: l q.t | andn m.t | ≠ 0 and m.st < q.st < m.et < q.et, wherein m.t is the effective time of the missing object m, m.st is the starting time of the effective time of the missing object m, q.st is the query starting time of the original query q, and m.et is the ending time of the effective time of the missing object m;
the set of candidate keywords CSdocThe conditions are satisfied: exists in the keyword set of the missing object and does not exist in the query keyword set of the original query, and is represented as:
4. The method for solving the why-not problem based on temporal perceptual objects as defined in claim 3,
for candidate keyword set CSdocEnumerating the keywords in (1), and adding the keywords selected by enumeration to the q.doc, comprising the following steps:
obtaining the candidate keyword set CSdocEach candidate key in the set ofThe edit distance between the query keyword sets q.doc of the original query;
and arranging the editing distances from small to large.
5. The method for solving the why-not problem based on temporal perceptual objects as defined in claim 1,
modifying q.doc, q.t and q.k in the original query q to q '. doc ', q '. t ' and q '. k ' such that the missing object set M appears in the query results of a refined query q ' (q.loc, q '. doc ', q '. t ', q '. k '), comprising the steps of:
under the second condition, the query time q.t of the original query is not modified, and only the query keyword q.doc and the query returned result number q.k of the original query are modified;
calculating the missing object M in the missing object set MiRanking R (q', m) in the refined query qi) And determining the ranking R (q', M) of the missing object set M according to the ranking;
the second condition is: l q.t | andd m.t | ≠ 0 and m.st < q.st, m.et > q.et, wherein m.t is the valid time of the missing object m, m.st is the start time of the valid time of the missing object m, q.st is the query start time of the original query q, m.et is the end time of the valid time of the missing object m, and q.et is the query end time of the original query q.
6. The method for solving the why-not problem based on temporal perceptual objects as defined in claim 1,
modifying q.doc, q.t and q.k in the original query q to q '. doc ', q '. t ' and q '. k ' such that the missing object set M appears in the query results of a refined query q ' (q.loc, q '. doc ', q '. t ', q '. k '), comprising the steps of:
under a third condition, fixing the query starting time q.st of the original query q, and gradually increasing the query ending time q.et of the original query q within a value range [ q.et, m.et ];
gradually increasing the value of the q.et by taking unit time as a step length;
for candidate keyword set CSdocEnumerating the keywords in the (1) and adding the keywords selected by enumeration to the q.doc;
the third condition is: l q.t ≠ m.t | ≠ 0 and q.st < m.st < q.et < m.et, where m.t is the valid time of the missing object m, m.st is the start time of the valid time of the missing object m, q.st is the query start time of the original query q, m.et is the end time of the valid time of the missing object m, and q.et is the query end time of the original query q.
7. The method for solving the why-not problem based on temporal perceptual objects as defined in claim 1,
modifying q.doc, q.t and q.k in the original query q to q '. doc ', q '. t ' and q '. k ' such that the missing object set M appears in the query results of a refined query q ' (q.loc, q '. doc ', q '. t ', q '. k '), comprising the steps of:
under the fourth condition, the query ending time q.et of the original query q is fixed, and the query starting time q.st of the original query q is gradually reduced within a value range (m.st, m.et);
gradually reducing the value of the q.st by taking unit time as a step length;
for candidate keyword set CSdocEnumerating the keywords in the (1) and adding the keywords selected by enumeration to the q.doc;
the fourth condition is: where | q.t |, andgate m.t | ═ 0 and m.et < q.st, where m.t is the valid time of the missing object m, m.st is the start time of the valid time of the missing object m, q.st is the query start time of the original query q, and m.et is the end time of the valid time of the missing object m.
8. The method for solving the why-not problem based on temporal perceptual objects as defined in claim 1,
modifying q.doc, q.t and q.k in the original query q to q '. doc ', q '. t ' and q '. k ' such that the missing object set M appears in the query results of a refined query q ' (q.loc, q '. doc ', q '. t ', q '. k '), comprising the steps of:
under the fifth condition, the query starting time q.st of the original query q is fixed, and the query ending time q.et of the original query q is gradually increased within a value range [ q.et, m.et ];
gradually increasing the value of the q.et by taking unit time as a step length;
the fifth condition is: l q.t | andno m.t | -0 and q.et < m.st, where m.t is the valid time of the missing object m, m.st. is the start time of the valid time of the missing object m, and q.et is the query end time of the original query q.
9. The method for solving the why-not problem based on temporal perceptual objects as defined in claim 1, wherein the step of calculating the modification cost of each of the refined queries q' comprises the steps of:
calculating a modification cost of the refined query q' according to a first formula;
selecting the refining query q' with the minimum modification cost as the optimal refining query;
the first formula:
the penalty (q, q ') is the modification cost of the refined query q ', namely the modification cost from the original query q to the refined query q ';
λ1、λ2、λ3respectively representing the modification preference parameters of the user for the query return result quantity q.k, the query keyword q.doc and the query time q.t, and setting lambda to be more than or equal to 0 and less than or equal to lambda1，λ2，λ31 or less and lambda1+λ2+λ3＝1；
Δk＝max(0,k’-k)，ΔkmaxIs the maximum modifier of q.k and is used to normalize Δ k to the interval [0,1 ]]；
Δ doc denotes the edit distance modified from q.doc to q '. doc' | Δ docmax| represents the maximum modified from q.doc to q.doc @The operation of major modification is carried out,
|Δdocmaxi for normalizing Delta doc to the interval [0,1 ]]；
Δ t denotes the modifier from q.t to q '. t', Δ tmaxRepresenting the maximum modification, at, over timemaxFor normalizing Δ t to the interval [0,1 ]]。
10. The method for solving the why-not problem based on temporal perceptual objects as defined in claim 9,
quantifying a cost of modification from the original query q to a refined query q' according to a first formula, comprising the steps of:
make it
Where xi is the same as [0,1 ]]Q.et is the query ending time of the original query, q.st is the query starting time of the original query, q '. et' is the query ending time of the refined query, and q '. st' is the query starting time of the refined query;
make it
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