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IE中的Nivo滑块显示问题(Nivo Slider Display Problem in IE)

我使用的是Nivo Slider,并且遇到了“堆叠”问题 - 所有图像最初都是相互重叠的。 我已经尝试了解决http://nivo.dev7studios.com/support/上所述的这个问题的解决方法,但这会导致图像在IE中完全不显示。 我也尝试了在style标签中包含“display:none”的解决方法,但是这在IE中具有相同的效果。 您可以在http://www.rooftopdrinker.com上查看目前没有解决方法的代码。 任何意见,将不胜感激。


I am using Nivo Slider, and am experiencing the "stacking" problem -- with all of the images initially loading on top of each other. I have tried the workaround for this problem described at http://nivo.dev7studios.com/support/ but this results in the images not displaying at all in IE. I have also tried the workaround of including "display:none" in the style tag but this has the same effect in IE. You can see the code, currently without the workaround, at http://www.rooftopdrinker.com. Any advice would be appreciated.


原文:https://stackoverflow.com/questions/6515365
更新时间:2023-07-18 15:07

最满意答案

UTL_MATCH包含匹配字符串和比较其相似性的方法。 编辑距离也称为Levenshtein距离,可能是一个很好的开始。 由于一个字符串是一个子字符串,它可能有助于比较相对于字符串大小的编辑距离。

--Addresses that are most similar to each substring.
select substring, address, edit_ratio
from
(
    --Rank edit ratios.
    select substring, address, edit_ratio
        ,dense_rank() over (partition by substring order by edit_ratio desc) edit_ratio_rank
    from
    (
        --Calculate edit ratio - edit distance relative to string sizes.
        select
            substring,
            address,
            (length(address) - UTL_MATCH.EDIT_DISTANCE(substring, address))/length(substring) edit_ratio
        from
        (
            --Fake addreses (from http://names.igopaygo.com/street/north_american_address)
            select '526 Burning Hill Big Beaver District of Columbia 20041'   address from dual union all
            select '5206 Hidden Rise Whitebead Michigan 48426'                address from dual union all
            select '2714 Noble Drive Milk River Michigan 48770'               address from dual union all
            select '8325 Grand Wagon Private Sleeping Buffalo Arkansas 72265' address from dual union all
            select '968 Iron Corner Wacker Arkansas 72793'                    address from dual
        ) addresses
        cross join
        (
            --Address substrings.
            select 'Michigan'           substring from dual union all
            select 'Not-So-Hidden Rise' substring from dual union all
            select '123 Fake Street'    substring from dual
        )
        order by substring, edit_ratio desc
    )
)
where edit_ratio_rank = 1
order by substring, address;

这些结果并不是很好,但希望这至少是一个很好的起点。 它应该适用于任何语言。 但是您仍然可能想要将其与某些语言或特定于语言环境的比较规则结合使用。

SUBSTRING          ADDRESS                                                  EDIT_RATIO
---------          -------                                                  ----------
123 Fake Street    526 Burning Hill Big Beaver District of Columbia 20041   0.5333
Michigan           2714 Noble Drive Milk River Michigan 48770               1
Michigan           5206 Hidden Rise Whitebead Michigan 48426                1
Not-So-Hidden Rise 5206 Hidden Rise Whitebead Michigan 48426                0.5

UTL_MATCH contains methods for matching strings and comparing their similarity. The edit distance, also known as the Levenshtein Distance, might be a good place to start. Since one string is a substring it may help to compare the edit distance relative to the size of the strings.

--Addresses that are most similar to each substring.
select substring, address, edit_ratio
from
(
    --Rank edit ratios.
    select substring, address, edit_ratio
        ,dense_rank() over (partition by substring order by edit_ratio desc) edit_ratio_rank
    from
    (
        --Calculate edit ratio - edit distance relative to string sizes.
        select
            substring,
            address,
            (length(address) - UTL_MATCH.EDIT_DISTANCE(substring, address))/length(substring) edit_ratio
        from
        (
            --Fake addreses (from http://names.igopaygo.com/street/north_american_address)
            select '526 Burning Hill Big Beaver District of Columbia 20041'   address from dual union all
            select '5206 Hidden Rise Whitebead Michigan 48426'                address from dual union all
            select '2714 Noble Drive Milk River Michigan 48770'               address from dual union all
            select '8325 Grand Wagon Private Sleeping Buffalo Arkansas 72265' address from dual union all
            select '968 Iron Corner Wacker Arkansas 72793'                    address from dual
        ) addresses
        cross join
        (
            --Address substrings.
            select 'Michigan'           substring from dual union all
            select 'Not-So-Hidden Rise' substring from dual union all
            select '123 Fake Street'    substring from dual
        )
        order by substring, edit_ratio desc
    )
)
where edit_ratio_rank = 1
order by substring, address;

These results are not great but hopefully this is at least a good starting point. It should work with any language. But you'll still probably want to combine this with some language- or locale- specific comparison rules.

SUBSTRING          ADDRESS                                                  EDIT_RATIO
---------          -------                                                  ----------
123 Fake Street    526 Burning Hill Big Beaver District of Columbia 20041   0.5333
Michigan           2714 Noble Drive Milk River Michigan 48770               1
Michigan           5206 Hidden Rise Whitebead Michigan 48426                1
Not-So-Hidden Rise 5206 Hidden Rise Whitebead Michigan 48426                0.5

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